README.md

Scikit-learn Tutorial

Original tutorial material from Jake VanderPlas

• email: [email protected]
• twitter: @jakevdp
• github: jakevdp

This repository contains notebooks and other files associated with the Scikit-learn tutorial. The notebooks have been updated by NeSI (http://github.com/nesi/sklearn_tutorial.git) to run with recent versions of Python and dependencies.

Recordings of the original workshop are available on Youtube:

• https://www.youtube.com/watch?v=L7R4HUQ-eQ0 (3 hours version)
• https://www.youtube.com/watch?v=HC0J_SPm9co (1.5 hours version)

Installation Notes

You can run the notebooks directly in your web browser at https://jennan.github.io/sklearn_tutorial_lite.

If you prefer to run on your own computer then we recommend that you download and install Miniconda. Once Miniconda is installed, navigate to your local copy of the repository and use the following command to create a Conda environment with all required packages:

conda env create -f environment_local.yml

Then activate your environment:

conda activate skl_tut

The tutorial material has been tested with the following package versions:

• Python version 3.10.5
• numpy version 1.22.4: https://www.numpy.org
• scipy version 1.8.1: https://www.scipy.org
• matplotlib version 3.5.2: https://matplotlib.org
• scikit-learn version 1.1.1: https://scikit-learn.org
• jupyterlab version 3.4.3: https://jupyterlab.readthedocs.io
• ipywidgets version 7.7.0: https://ipywidgets.readthedocs.io
• pandas version 1.4.2: https://pandas.pydata.org/

Downloading the Tutorial Materials

We have already installed all the notebooks on NeSI JupyterHub. However, if you prefer to run on your laptop, you will need to clone the repository:

git clone https://github.com/nesi/sklearn_tutorial.git

Note also that some of the code in these notebooks will not work outside the directory structure of this tutorial, so it is important to clone the full repository if possible.

Notebook Listing

If you have followed the installation instructions to run on your laptop, start JupyterLab:

jupyter lab 

Then navigate the directory structure. The notebooks are under the directory notebooks. Click on Index.ipynb to get started.